{"id":"W2293797001","doi":"10.3390/pr4010006","title":"Surrogate Models for Online Monitoring and Process Troubleshooting of NBR Emulsion Copolymerization","year":2016,"lang":"en","type":"article","venue":"Processes","topic":"Process Optimization and Integration","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Troubleshooting; Surrogate model; Copolymer; Emulsion; Process (computing); Process engineering; Computer science; Natural rubber; Biological system; Materials science; Polymer; Biochemical engineering; Chemical engineering; Engineering; Machine learning; Composite material","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008588895,0.0007111584,0.0007296705,0.0003395008,0.000173218,0.0006715267,0.0004335259,0.0006319071,0.0007846771],"category_scores_gemma":[0.00223011,0.0003518783,0.0005493973,0.0002552278,0.0002709019,0.0005009565,0.0004037153,0.0007212301,0.0001999551],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004370941,"about_ca_system_score_gemma":0.0006863775,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001072225,"about_ca_topic_score_gemma":0.001198097,"domain_scores_codex":[0.9995824,0.0001314845,0.00002628323,0.00006317803,0.0001630929,0.00003351663],"domain_scores_gemma":[0.9992782,0.0003930151,0.0001573717,0.00005729774,0.00009296458,0.00002121858],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001321199,0.00006971588,0.0004242999,0.00008478312,0.00001561662,0.00002871278,0.00001489426,0.9644634,0.02148586,0.001816794,0.0001365984,0.01132719],"study_design_scores_gemma":[0.000003913439,0.00004957708,0.0001185225,0.000002700867,0.000003258619,0.000005000135,0.000001757038,0.9912492,0.007951506,0.0004042639,0.0002064453,0.000003777412],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1007946,0.0004600947,0.8946307,0.0001129532,0.00003160464,0.0001009713,0.0002428145,0.0006121297,0.003014215],"genre_scores_gemma":[0.9125414,0.0005200532,0.08408703,0.00003623239,0.000008979031,0.0002281811,0.0003580489,0.00006613973,0.002153914],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001072225,"threshold_uncertainty_score":0.004542291,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02194193078598322,"score_gpt":0.2621965726650423,"score_spread":0.2402546418790591,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}